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neither guaranteed (optimism) nor impossible (pessimism). MePhiS aims at (1) reinterpreting ethical and other philosophical issues by emphasizing their entanglement with suffering; (2) integrating
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neither guaranteed (optimism) nor impossible (pessimism). MePhiS aims at (1) reinterpreting ethical and other philosophical issues by emphasizing their entanglement with suffering; (2) integrating
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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intelligence in engineering Interest in multi-objective optimization and machine learning Strong background in computational engineering, engineering mathematics and / or computer aided design High
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from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular
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CMOS technology can be employed for optimization of the transparency of the Schottky barrier and for promoting performance of Josephson field-effect transistors (JoFETs). With sufficient coherence
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will be involved in the design, fabrication, and testing of functional thin film coatings. Key responsibilities include: Developing and optimizing advanced surfaces using state-of-the-art thin film
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optimization, cell component manufacturing, and the testing of solid-state battery performance. This role involves intense collaboration with international partners and the dissemination of results within the EU
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and power converters. Our work spans from fundamental modelling and analysis to advanced control design and system optimization. Our specialty is developing embedded control, estimation, and
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the opportunity to visit various partners in the network. The goal is to explore new synergies between natural language–based human-AI interaction, nature-inspired optimization and exploration